The development of the smart ocean requires that various features of the ocean be explored
and understood. The Underwater Internet of Things (UIoT), an extension of the Internet of …

In the emerging field of acoustic novelty detection, most research efforts are devoted to
probabilistic approaches such as mixture models or state‐space models. Only recent studies …

Underwater target classification using passive sonar remains a critical issue due to the
changeable ocean environment. Convolutional neural networks (CNNs) have shown …

In past decades, we witnessed many applications and fast development of cloud computing
technologies. Cloud faults are encountered in a cloud computing environment. They badly …

<? Pub Dtl=""?> Traditional feature extractions, such as mel-frequency cepstral coefficients
(MFCCs), are susceptible to acoustic channel effects, reverberation, and additive …

A novel MIMO homogeneous Super-Twisting Algorithm is proposed in this paper for
nonlinear systems with relative degree one, having a time and state-varying uncertain …

Hand-craft features and clustering algorithms constitute the main parts of the unsupervised
clustering system. Performance of the clustering deteriorates when the assumed …

In seafloor mining environments, ultrasonic detection is often used for underwater target
recognition, and a large number of suspended particles reduce the recognition rate of single …

This document describes a distance measurement system for underwater applications with
computer vision and an Artificial Neural Network (ANN). The developed system is installed …

Spectrum is one of the commonly used but effective feature for underwater acoustic target
classification. However, features extracted based on the spectra are vulnerable to the …